Machine Learning: MCQs Set – 04

Machine Learning: MCQs Set – 04

Q31: Supervised learning differs from unsupervised clustering. Supervised learning requires

  • (A) At least one input attribute
  • (B) Input attributes to be categorical
  • (C) At least one output attribute
  • (D) Output attributes to be categorical

Q32: Which data is used to tune the parameters of supervised learning model

  • (A) training
  • (B) test
  • (C) verification
  • (D) validation

Q33: For two real-valued attributes, the correlation coefficient is 0.85. What does this value indicate?

  • (A) The attributes are not linearly related
  • (B) As the value of one attribute increases the value of the second attribute also increases
  • (C) As the value of one attribute decreases the value of the second attribute increases
  • (D) The attributes show a curvilinear relationship

Q34: Which of the following is not TRUE for regression?

  • (A) It relates inputs to outputs
  • (B) It is used for prediction
  • (C) It may be used for interpretation
  • (D) It discovers causal relationships

Q35: Assume you’re given three variables: X, Y, and Z. C1, C2, and C3 are the Pearson correlation coefficients for (X, Y), (Y, Z), and (X, Z), respectively. You have now added 2 to all X values (i.e. new values are X+2), removed 2 from all Y values (i.e. new values are Y-2) and Z remains the same. D1, D2, and D3 are the new coefficients for (X,Y), (Y,Z), and (X,Z). How do the values of D1, D2, and D3 relate to the values of C1, C2, and C3?

  • (A) D1= C1, D2 < C2, D3 > C3
  • (B) D1 = C1, D2 > C2, D3 > C3
  • (C) D1 = C1, D2 > C2, D3 < C3
  • (D) D1 = C1, D2 = C2, D3 = C3

Q36: Which neural network architecture would be most suited to handle an image identification problem (recognizing a dog in a photo)?

  • (A) Multi Layer Perceptron
  • (B) Convolutional Neural Network
  • (C) Recurrent Neural network
  • (D) Perceptron

Q37: Assume we train a hard-margin linear SVM in R2 on n > 100 data points, resulting in a hyperplane with precisely two support vectors. What is the maximum number of support vectors for the new hyperplane if we add one more data point and retrain the classifier (assuming the n + 1 points are linearly separable)?

  • (A) 2
  • (B) n
  • (C) 3
  • (D) n+1

Q38: Assume you’ve been given a variable V, as well as its mean and median. Based on these numbers, you may determine if the variable “V” is skewed to the left or right given the criterion mean(V) > median (V)

  • (A) TRUE
  • (B) FALSE

Q39: A fair six-sided die is rolled twice. What is the probability of getting 2 on the first roll and not getting 4 on the second roll?

  • (A) 1/36
  • (B) 1/18
  • (C) 5/36
  • (D) 1/6

Q40: Some test results are normally distributed, with a mean of 18 and a standard deviation of 6. What percentage of test takers scored between 18 and 24?

  • (A) 20%
  • (B) 22%
  • (C) 34%
  • (D) None of the above